• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.251-263
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• 2019

Sentinel-2 Multi Spectral Instrument(MSI) launched by the European Space Agency (ESA) offered high spatial resolution optical products, enhanced temporal revisit of five days, and 13 spectral bands in the visible, near infrared and shortwave infrared wavelengths similar to Landsat mission. Landsat satellite imagery has been applied to various previous studies, but Sentinel-2 optical satellite imagery has not been widely used. Currently, for global coverage, Sentinel-2 products are systematically processed and distributed to Level-1C (L1C) products which contain the Top-of-Atmosphere (TOA) reflectance. Furthermore, ESA plans a systematic global production of Level-2A(L2A) product including the atmospheric corrected Bottom-of-Atmosphere (BOA) reflectance considered the aerosol optical thickness and the water vapor content. Therefore, the Sentinel-2 L2A products are expected to enhance the reliability of image quality for overall coverage in the Sentinel-2 mission with enhanced spatial,spectral, and temporal resolution. The purpose of this work is a quantitative comparison Sentinel-2 L2A products and fully simulated image to evaluate the applicability of the Sentinel-2 dataset in cultivated land growing various kinds of crops in Korea. Reference image of Sentinel-2 L2A data was simulated by airborne hyperspectral data acquired from AISA Fenix sensor. The simulation imagery was compared with the reflectance of L1C TOA and that of L2A BOA data. The result of quantitative comparison shows that, for the atmospherically corrected L2A reflectance, the decrease in RMSE and the increase in correlation coefficient were found at the visible band and vegetation indices to be significant.

• Journal of Food Hygiene and Safety
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• v.37 no.3
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• pp.143-148
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• 2022

This study was to investigate an analytical method for determining dieckol content in Ecklonia stolonifera extract. According to the guidelines of International Conference on Harmonization. Method validation was performed by measuring the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of dieckol using high-performance liquid chromatography-photodiode array. The results showed that the correlation coefficient of calibration curve (R²) for dieckol was 0.9997. The LOD and LOQ for dieckol were 0.18 and 0.56 ㎍/mL, respectively. The intra- and inter-day precision values of dieckol were approximately 1.58-4.39% and 1.37-4.64%, respectively. Moreover, intra- and inter-day accuracies of dieckol were approximately 96.91-102.33% and 98.41-105.71%, respectively. Thus, we successfully validated the analytical method for estimating dieckol content in E. stolonifera extract.

• Applied Chemistry for Engineering
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• v.7 no.5
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• pp.877-887
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• 1996

The ideal membranes for membrane-covered oxygen probes system should be selectively permeable for oxygen and chemically inert, and have good mechanical strength. Polysulfone(PSf) was selected to develop the membrane for membrane-covered oxygen electrodes system. PSf membranes have properties such as good reproducibility, good mechanical strength, chemical inertness, and high heat resistance. PSf membranes were cast from polymer solution on the glass plate at constant temperature, and casting solvents used were tetrahydrofuran(THF), methylene chloride, and N-methyl-2-pyrrolidone(NMP). Tricresyl phosphate(TCP) as plasicizer was added to PSf to increase the softness of membrane. The permeation characteristics were observed for pure oxygen and nitrogen through pure PSf membranes by variable volume method and membrane-covered electrode system. The permeability coefficients of oxygen and nitrogen measured by variable volume method were slightly decreased with increasing of upstream pressure. The permeation properties of PSf membrane using methylene choride as casting solvent were not affected by the PSf amount of polymer solution. The permeability coefficients of oxygen and nitrogen for PSf membrane containing TCP were very slightly lower than those for pure PSf membrane, but ideal separation factors were slightly higher. The flexibility of PSf membrane containing 2wt% TCP was better than that of pure PSf membrane. It was expected that this increase in flexibility would solve the difficulty of fixing the membrane to the cathode. The membrane-covered oxygen probes system was composed of anode, cathode and electrolyte. The type of the anode was Ag/AgCl half-cell, that of cathode was Ag, and the electrolyte was 4N KCl solution. The result of sampled current voltametry for PSf membrane showed the plateu region at -0.3V~-1.0V. The correlation coefficient of oxygen partial pressure versus current for PSf membrane was relatively high, 0.99949. It was concluded that PSf membrane was the good candidate for the membrane-covered oxygen probes system.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Economic and Environmental Geology
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• v.51 no.1
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• pp.27-38
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• 2018

Groundwaters in different rock types (Mesozoic granite, Precambrian gneiss, and schist) of Ganghwa island, Incheon City were characterized by using naturally occurring radioactive materials (NORM) and hydrogeochemical constituents. For the study, groundwater samples from 69 wells had been collected over eight years. Statistical methods were applied to relate hydrogeochemical components and NORM in the groundwater samples. The groundwater samples belonged to $Ca(Na)-HCO_3$ types. The uranium concentrations in three groundwater samples exceeded 30 ug/L of United States Environmental Protection Agency (US EPA) maximum contaminant level (MCL). The radon concentrations in 28 groundwater samples exceeded 4,000 pCi/L (picocuries per Liter) of US EPA alternative maximum contaminant level (AMCL). Gross-alpha in all the groundwater samples did not exceed 15 pCi/L of US EPA MCL. The average concentrations of uranium and radon in groundwater were the highest in granite area, and then gneiss, schist areas in order. In schist area, the correlation coefficient (R) between radon and $HCO_3$ is -0.40 and R between uranium and $SO_4$ is 0.54. In gneiss area, the R between radon and uranium is 0.55 and the R between uranium and $SO_4$ is 0.41. According to factor analysis, each geological area shows different chemical characteristics. The statistical analysis of whole groundwater resulted in nearly no significant relationship among uranium, radon and chemical constituents. Subsequently, more detailed studies on hydrogeological, geochemical, and geological characteristics related to NORM are required to better understand the behavior and fate of NORM.

• Journal of the korean academy of Pediatric Dentistry
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• v.31 no.2
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• pp.190-201
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• 2004

The aim of this study was to evaluate the resistance to degradation and to compare the wear resistance characteristics of four esthetic restorative materials in an alkaline solution. The brands studied were Charmfil, Charmfil flow(composite resin), Compoglass F and PrimaFlow(compomer). The results were as follows: 1. The mass loss were not significantly different among the materials(p>0.05). 2. The sequence of the degree of degradation layer depth was in descending order by Compoglass F, PrimaFlow, Charmfil, and Charmfil flow. There were significant differences between Compoglass F and the others(p<0.05). 3. The sequence of the Si loss was in descending order by Charmfil flow, Charmfil, PrimaFlow, and Compoglass F. There were significant differences among these materials(p<0.05). 4. When observed with SEM, destruction of bonding between matrix and filler was observed and when observed with CLSM, the depth of degradation layer of specimen surface was observed. 5. The sequence of maximum wear depth was in descending order by Comfoglass, PrimaFlow Charmal, and Charmfil flow. There were significant differences among these materials(p<0.05). 6. The correlation coefficient between Si loss and degradation layer depth (r=0.602, p<0.05) Vicker's hardness number and maximum wear depth (r=0.501, p<0.05) were relatively high. These results indicate that wear and hydrolytic degradation may be considered to be evaluation factors of composite resins and compomers.

• The Korean Journal of Pesticide Science
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• v.8 no.3
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• pp.151-161
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• 2004

Three dimensional quantitative structure-activity relationships (3D-QSAR) studies for the protox inhibition activities against root and shoot of rice plant (Orysa sativa L.) and barnyardgrass (Echinochloa crus-galli) by a series of new A=3,4,5,6-tetrahydrophthalimino, B=3-chloro-4,5,6,7-tetrahydro-2H-indazolyl and C=3,4-dimethylmaleimino group, and R-group substituted on the phenyl ring in 1-(5-methyl-3-phenylisoxazolin-5-yl)methoxy-2chloro-4-fluorobenzene derivatives were performed using comparative molecular field analyses (CoMFA) methodology with Gasteiger-Huckel charge. Four CoMFA models for the protox inhibition activities against root and shoot of the two plants were generated using 46 molecules as training set and the predictive ability of the each models was evaluated against a test set of 8 molecules. And the statistical results of these models with combination (SIH) of standard field, indicator field and H-bond field showed the best predictability of the protox inhibition activities based on the cross-validated value $r^2_{cv.}$ $(q^2=0.635\sim0.924)$, conventional coefficient $(r^2_{ncv.}=0.928\sim0.977)$ and PRESS value $(0.091\sim0.156)$, respectively. The activities exhibited a strong correlation with steric $(74.3\sim87.4%)$, electrostatic $(10.10\sim18.5%)$ and hydrophobic $(1.10\sim8.30%)$ factors of the molecules. The steric feature of molecule may be an important factor for the activities. We founded that an novel selective and higher protox inhibitors between the two plants may be designed by modification of X-subsitutents for barnyardgrass based upon the results obtained from CoMFA analyses.

• The korean journal of orthodontics
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• v.27 no.1
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• pp.65-78
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• 1997

This study was carried out in order to determine soft tissue response to incisor movement and mandibular repositioning and to determine feasibility of predicting vertical and horizontal changes in soft tissue with hard tissue movement. For this study, cephalometric records of 41 orthodontically treated adult females who had Angle's Class II division 1 malocclusion were selected and stepwise multiple regression analysis was employed. Following conclusions were obtained by analysing the changes of soft tissue and hard tissue before and after treatment. 1. Hard tissue measurements that showed significant changes before and after treatment were horizontal and angular changes of maxillary incisor, horizontal,vertical and angular changes of mandibular incisor, overjet, overbite, interincisal angle, mandibular repositioning, A,B, skeletal convexity and soft tissue measurements that showed significant changes were horizontal, thickness and angular changes of upper lip, horizontal and angular changes of lower lip, interlabial angle, nasolabial angle labiomental angle, Sri, Ss, Si and soft tissue convexity(P<0.05). 2. All Soft tissue measurements changed significantly before and after treatment had between one and four hard tissue independent variables at statistically significant level, indicating that all soft tissue changes were direct relationship with hard tissue changes 3. Ova jet, horizontal change of maxillary incisor, horizontal change of maxillary root apex and horizontal change of pogonion entered into prediction equations most frequentely indicating that they were more significant variables in prediction of vertical and horizontal changes in the soft tissue with treatment, but vertical changes of mandibular incisor not entered any prediction equations, indicating that it was not considered a good predictor for soft tissue changes with maxillary incisor retraction. 4. Horizontal and vertical changes in subnasale were found to have most independent variables, significant at the 0.05 level in prediction-equations(${\Delta}$Sn(H):Ur, Is(H), Pg(H), UIA,${\Delta}$Sn(V): Is(H), Pg(H), overjet, A), indicating that subnasale changes are influenced by complex hard tissue interaction. 5. Multiple correlation coefficient($R^2$) of the soft tissue prediction equations ranges from 0.2-0.6.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.1
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• pp.50-57
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• 2016

This study was conducted to determine the effect of mathematical transformation on near infrared spectroscopy (NIRS) calibrations for the prediction of chemical composition and fermentation parameters in corn silage. Corn silage samples (n=407) were collected from cattle farms and feed companies in Korea between 2014 and 2015. Samples of silage were scanned at 1 nm intervals over the wavelength range of 680~2,500 nm. The optical data were recorded as log 1/Reflectance (log 1/R) and scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with several spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation ($R^2{_{cv}}$) and the lowest standard error of cross validation (SECV). Results of this study revealed that the NIRS method could be used to predict chemical constituents accurately (correlation coefficient of cross validation, $R^2{_{cv}}$, ranging from 0.77 to 0.91). The best mathematical treatment for moisture and crude protein (CP) was first-order derivatives (1, 16, 16, and 1, 4, 4), whereas the best mathematical treatment for neutral detergent fiber (NDF) and acid detergent fiber (ADF) was 2, 16, 16. The calibration models for fermentation parameters had lower predictive accuracy than chemical constituents. However, pH and lactic acids were predicted with considerable accuracy ($R^2{_{cv}}$ 0.74 to 0.77). The best mathematical treatment for them was 1, 8, 8 and 2, 16, 16, respectively. Results of this experiment demonstrate that it is possible to use NIRS method to predict the chemical composition and fermentation quality of fresh corn silages as a routine analysis method for feeding value evaluation to give advice to farmers.